Intestinal Ultrasound for the Pediatric Gastroenterologist
Bibliographic record
Abstract
Crohn disease and ulcerative colitis are chronic inflammatory bowel diseases (IBD) often diagnosed in childhood. A strict monitoring strategy can potentially alter the disease course and facilitate early effective treatment before irreversible bowel damage occurs. Serial colonoscopy in children, the gold standard for monitoring, is impractical. Accurate, real-time, noninvasive markers of disease activity are needed. Intestinal ultrasound is an accurate, noninvasive, real-time, point-of-care, cross-sectional imaging tool used to monitor inflammation in pediatric IBD patients in Europe, Canada, and Australia. It is now emerging in a few expert centers in the United States as a safe, non-radiating, inexpensive, bedside tool used by the treating gastroenterologist for real-time decision-making. Unlike the standard biomarkers of pediatric IBD activity, C-reactive protein, and fecal calprotectin, intestinal ultrasound (IUS) facilitates disease localization, characterizes severity, extent, and accurately detects complications. Perhaps most importantly, IUS may enhance shared understanding and ease the burden of treatment decision-making for both the gastroenterologist and the patient. There is a lack of standardization for bedside IUS among pediatric gastroenterologists. The purpose is to outline a standardized approach to pediatric bedside IUS, including basic equipment requirements and technique, patient selection, preparation and positioning, technical considerations and limitations, documentation of mesenteric and luminal features of IBD, characterization of penetrating disease and strictures, and provide a proposed pediatric IUS monitoring algorithm to guide care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".